I JMIR出版物V 21% N 12% P e14909 %T验证单卡塔尔世界杯8强波胆分析中心预移动心房颤动应用程序在真实环境中用于持续监测心房颤动:中试队列研究%A张辉%A张杰%A李红宝%A陈一欣%A杨斌%A郭玉涛%A陈云代%+中国人民解放军总医院心内科，北京100853,86 13810021492,guoyutao2010@126.com %K房颤%K光容量血流谱%K连续检测%K精度%K智能手机%K智能带%K算法%D 2019 %7 3.12.2019 %9原创论文%J J医学互联网Res %G英文%X心房颤动是临床上最常见的反复发作的心律失常，大多数临床事件发生在院外。低检出率和不遵守指导方针是心房颤动管理的主要障碍。光容量描记术是一种用于房颤筛查的新技术。然而，基于光容积描记术的智能设备用于心房颤动检测及其影响检测的潜在临床因素的验证有限。目的:本研究旨在探索基于光容积描记术的智能设备在现实环境中检测心房颤动的可行性。方法:于2018年9月14日至10月16日招募年龄≥18岁(n=361)的受试者，使用基于光容积描记术的智能可穿戴设备(即智能手环或智能手表)主动测量筛查心房颤动，由用户发起。其中200名受试者还使用智能腕带进行了14天的自动定期监测。基线诊断为“疑似”房颤，经心电图和体检确认。 The sensitivity and accuracy of photoplethysmography-based smart devices for monitoring atrial fibrillation were evaluated. Results: A total of 2353 active measurement signals and 23,864 periodic measurement signals were recorded. Eleven subjects were confirmed to have persistent atrial fibrillation, and 20 were confirmed to have paroxysmal atrial fibrillation. Smart devices demonstrated >91% predictive ability for atrial fibrillation. The sensitivity and specificity of devices in detecting atrial fibrillation among active recording of the 361 subjects were 100% and about 99%, respectively. For subjects with persistent atrial fibrillation, 127 (97.0%) active measurements and 2240 (99.2%) periodic measurements were identified as atrial fibrillation by the algorithm. For subjects with paroxysmal atrial fibrillation, 36 (17%) active measurements and 717 (19.8%) periodic measurements were identified as atrial fibrillation by the algorithm. All persistent atrial fibrillation cases could be detected as “atrial fibrillation episodes” by the photoplethysmography algorithm on the first monitoring day, while 14 (70%) patients with paroxysmal atrial fibrillation demonstrated “atrial fibrillation episodes” within the first 6 days. The average time to detect paroxysmal atrial fibrillation was 2 days (interquartile range: 1.25-5.75) by active measurement and 1 day (interquartile range: 1.00-2.00) by periodic measurement (P=.10). The first detection time of atrial fibrillation burden of <50% per 24 hours was 4 days by active measurement and 2 days by periodic measurementThe first detection time of atrial fibrillation burden of >50% per 24 hours was 1 day for both active and periodic measurements (active measurement: P=.02, periodic measurement: P=.03). Conclusions: Photoplethysmography-based smart devices demonstrated good atrial fibrillation predictive ability in both active and periodic measurements. However, atrial fibrillation type could impact detection, resulting in increased monitoring time. Trial Registration: Chinese Clinical Trial Registry of the International Clinical Trials Registry Platform of the World Health Organization ChiCTR-OOC-17014138; http://www.chictr.org.cn/showprojen.aspx?proj=24191. %M 31793887 %R 10.2196/14909 %U //www.mybigtv.com/2019/12/e14909 %U https://doi.org/10.2196/14909 %U http://www.ncbi.nlm.nih.gov/pubmed/31793887